import os
from functools import wraps
from uuid import uuid4

import boto3

from moto import mock_aws


def dynamodb_aws_verified(
    create_table: bool = True,
    add_range: bool = False,
    numeric_range: bool = False,
    add_gsi: bool = False,
    add_gsi_range: bool = False,
    gsi_projection_type: str = "ALL",
    add_lsi: bool = False,
    lsi_projection_type: str = "ALL",
    numeric_gsi_range: bool = False,
    numeric_lsi_range: bool = False,
):
    """
    Function that is verified to work against AWS.
    Can be run against AWS at any time by setting:
      MOTO_TEST_ALLOW_AWS_REQUEST=true

    If this environment variable is not set, the function runs in a `mock_aws` context.

    This decorator will:
      - Create a table
      - Run the test and pass the table_name as an argument
      - Delete the table
    """

    def inner(func):
        @wraps(func)
        def pagination_wrapper(**kwargs):
            table_name = "T" + str(uuid4())[0:6]
            if create_table:
                kwargs["table_name"] = table_name

            def create_table_and_test():
                client = boto3.client("dynamodb", region_name="us-east-1")

                range_type = "N" if numeric_range else "S"
                gsi_range_type = "N" if numeric_gsi_range else "S"
                lsi_range_type = "N" if numeric_lsi_range else "S"

                db_kwargs = {
                    "KeySchema": [{"AttributeName": "pk", "KeyType": "HASH"}],
                    "AttributeDefinitions": [
                        {"AttributeName": "pk", "AttributeType": "S"}
                    ],
                }
                if add_range or numeric_range:
                    db_kwargs["KeySchema"].append(
                        {"AttributeName": "sk", "KeyType": "RANGE"}
                    )
                    db_kwargs["AttributeDefinitions"].append(
                        {"AttributeName": "sk", "AttributeType": range_type}
                    )
                if add_gsi:
                    db_kwargs["GlobalSecondaryIndexes"] = [
                        {
                            "IndexName": "test_gsi",
                            "KeySchema": [
                                {"AttributeName": "gsi_pk", "KeyType": "HASH"},
                            ],
                            "Projection": {"ProjectionType": gsi_projection_type},
                            "ProvisionedThroughput": {
                                "ReadCapacityUnits": 1,
                                "WriteCapacityUnits": 1,
                            },
                        }
                    ]
                    db_kwargs["AttributeDefinitions"].append(
                        {"AttributeName": "gsi_pk", "AttributeType": "S"}
                    )
                if add_gsi_range or numeric_gsi_range:
                    db_kwargs["GlobalSecondaryIndexes"] = [
                        {
                            "IndexName": "test_gsi",
                            "KeySchema": [
                                {"AttributeName": "gsi_pk", "KeyType": "HASH"},
                                {"AttributeName": "gsi_sk", "KeyType": "RANGE"},
                            ],
                            "Projection": {"ProjectionType": gsi_projection_type},
                            "ProvisionedThroughput": {
                                "ReadCapacityUnits": 1,
                                "WriteCapacityUnits": 1,
                            },
                        }
                    ]
                    db_kwargs["AttributeDefinitions"].append(
                        {"AttributeName": "gsi_pk", "AttributeType": "S"}
                    )
                    db_kwargs["AttributeDefinitions"].append(
                        {"AttributeName": "gsi_sk", "AttributeType": gsi_range_type}
                    )
                if add_lsi or numeric_lsi_range:
                    db_kwargs["LocalSecondaryIndexes"] = [
                        {
                            "IndexName": "test_lsi",
                            "KeySchema": [
                                {"AttributeName": "pk", "KeyType": "HASH"},
                                {"AttributeName": "lsi_sk", "KeyType": "RANGE"},
                            ],
                            "Projection": {"ProjectionType": lsi_projection_type},
                        }
                    ]
                    db_kwargs["AttributeDefinitions"].append(
                        {"AttributeName": "lsi_sk", "AttributeType": lsi_range_type}
                    )
                client.create_table(
                    TableName=kwargs["table_name"],
                    ProvisionedThroughput={
                        "ReadCapacityUnits": 1,
                        "WriteCapacityUnits": 5,
                    },
                    Tags=[{"Key": "environment", "Value": "moto_tests"}],
                    **db_kwargs,
                )
                waiter = client.get_waiter("table_exists")
                waiter.wait(TableName=kwargs["table_name"])
                try:
                    resp = func(**kwargs)
                finally:
                    ### CLEANUP ###
                    client.delete_table(TableName=kwargs["table_name"])

                return resp

            allow_aws_request = (
                os.environ.get("MOTO_TEST_ALLOW_AWS_REQUEST", "false").lower() == "true"
            )

            if allow_aws_request:
                if create_table:
                    print(f"Test {func} will create DDB Table {table_name}")  # noqa
                    return create_table_and_test()
                else:
                    return func(**kwargs)
            else:
                with mock_aws():
                    if create_table:
                        return create_table_and_test()
                    else:
                        return func(**kwargs)

        return pagination_wrapper

    return inner
